Biology subjects

Anderson, T. K.

Publications and source records attributed to Anderson, T. K..

At least 19 recordsLinked to original sources

bioRxiv2026

Host type governs influenza evolutionary strategy across reservoir and spillover hosts

Despite its high propensity for host switching, the evolutionary mechanisms underlying influenza host adaptation remain unclear. H3Nx influenza viruses are uniquely generalist, with long-term lineages that circulate in avian, human, swine, equine, and canine hosts. Using 13,295 H3Nx sequences, we quantified host-specific adaptive evolution and developed a pipeline to map reassortment events onto trees with measures of statistical uncertainty. We find that while H3Nx viruses in mammals undergo adaptive evolution in HA and NA, viruses in birds experience very little directional selection. Instead, avian lineages exhibit high rates of reassortment, frequently generating novel reassortant lineages that persist transiently and turn over rapidly. 29.8-47.4% of all avian reassortant lineages are purged within the first year of circulation, and reassortment shows no fitness benefit in birds. In contrast, reassorted lineages in swine are more likely to persist long-term, suggesting that reassortment in swine may be broadly beneficial. Segment-specific reassortment patterns were also distinct between avian and mammalian viruses, with NA reassorting more frequently than expected in birds, but less frequently than expected in swine. Reassortment events are enriched between mammalian, but not avian, host switches, suggesting that reassortment may be most beneficial for mediating host switches among mammalian species. Together, our data suggest that host differences drive fundamentally different evolutionary outcomes for influenza viruses, transitioning from reassortment-dominant evolution in their avian reservoir, to varying degrees of adaptation upon establishment in mammals.

evolutionary biology↗

bioRxiv2026

The nucleoside analog CMX521 inhibits coronavirus RNA-dependent RNA polymerase via a two-pronged mechanism

The SARS-CoV-2 pandemic has underscored the urgent need for broad-spectrum antivirals in pandemic preparedness efforts. Nucleoside analogs targeting viral polymerases are often considered in this context. Here, we employ ensemble biochemical assays and single-molecule magnetic tweezers to characterize the detailed mechanism of action of the adenosine analog CMX521 (developed through Phase 1 clinical studies), a broad-spectrum antiviral against caliciviruses and coronaviruses, against SARS-CoV-2 RNA-dependent RNA polymerase (RdRp). The triphosphate form of CMX521 is efficiently incorporated by RdRp, even against saturating ATP concentrations. Analog incorporation induces only a brief pause in nascent RNA synthesis. When embedded in the template strand, CMX521 causes the polymerase to stall [~]9 s on average due to impaired uridine opposite incorporation. Multiple CMX521 residues in the template strand completely inhibit polymerase elongation. When the coronavirus polymerase is associated with the viral helicase, CMX521 strongly promotes copy-back RNA synthesis suggesting a second inhibitory mechanism for CMX521. Collectively, our findings establish a two-pronged mode of coronavirus polymerase inhibition by CMX521.

microbiology↗

bioRxiv2026

Quantifying Asymmetric Coevolutionary Dynamics using Normalized Phylogenetic Costs

AO_SCPLOWBSTRACTC_SCPLOWCoevolutionary studies aim to characterize associations, such as virus-host relationships, by using phylogenetic distances to quantify the topological concordance between the phylogenies of interacting taxa. However, phylogenetic distances cannot capture asymmetrical relationships that arise from differences in sampling, evolutionary rates, or characterizations between datasets. Furthermore, a lack of accurate normalization complicates the interpretation and validation of coevolutionary analyses. To address these limitations, we employed the Asymmetric Cluster Affinity and Cluster Support costs as a general framework to quantify coevolutionary patterns across multiple biological scales. We benchmarked the precision of these costs by reanalyzing a curated dataset documenting interspecies transmission frequencies across nineteen virus-host phylogenies. Our results corroborate prior findings showing that all virus families under study can cross species boundaries; however, the asymmetric costs provide a more granular representation, demonstrating that the frequency of such events varies significantly across families. We then applied the Asymmetric Cluster Support cost to quantify preferential gene segment pairings within the Bluetongue virus genome. This analysis revealed a close phylogenetic association between the outer capsid proteins VP2 and VP5, likely reflecting shared selective pressures due to their critical roles in cell entry and exit. In contrast, gene segments encoding nonstructural proteins exhibited discordant evolutionary histories relative to other segments. Finally, we demonstrated that the Asymmetric Cluster Support cost can detect coevolutionary dynamics in swine influenza A virus, identifying novel gene pairings indicative of major viral reassortment events. Overall, our approach demonstrates that normalized asymmetric phylogenetic costs accurately capture complex biological relationships and provide a robust framework for quantifying fine-scale coevolutionary dynamics in rapidly evolving pathogens.

bioinformatics↗

bioRxiv2026

PREMISE: A Quality-Aware Probabilistic Framework for Pathogen Resolution and Source Assignment in Viral mNGS

The circulation of Influenza A viruses (IAVs) in wildlife and livestock presents a significant public health threat due to their zoonotic potential and rapid genomic diversification. Accurate classification of viral subtypes and characterization of within-host diversity are crucial for risk assessment and vaccine development. Although metagenomic sequencing facilitates early detection, prevalent memory-efficient k-mer-based pipelines often discard critical linkage information. This loss of information can result in missed or imprecise pathogen identification, potentially delaying clinical and public health responses. We introduce PREMISE (Pathogen Resolution via Expectation Maximization In Sequencing Experiments), a probabilistic, alignment-based framework implemented in RUST for high-resolution viral genome identification. By integrating advanced string data structures for efficient alignment with a quality-score-aware Expectation-Maximization algorithm, PREMISE accurately identifies source strains, estimates relative abundances, and performs precise read assignments. This framework provides superior source estimation with statistical confidence, enabling the identification of mixed infections, recombination, and IAV-reassortment directly from raw data. Validated against simulated and empirical datasets, PREMISE outperforms state-of-the-art k-mer methods. Ultimately, this framework represents a significant advancement in viral identification, providing a foundation for novel approaches that can automatically flag reassorted viruses or recombination events in the future, thereby improving the detection of emerging pathogens with zoonotic potential. Availabilityhttps://github.com/sriram98v/premise under a MIT license. Contactsriramv@iastate.edu

bioinformatics↗

bioRxiv2026

Splicer: Phylogenetic Placement in Sub-Linear Time

MotivationPhylogenetic placement is an established approach for rapidly classifying new genetic sequences and updating a phylogeny without fully recomputing it. Popular maximum-likelihood placement methods, such as pplacer and EPA-ng, tend to struggle computationally when the size of the reference tree increases to tens or hundreds of thousands of sequences. As a more scalable alternative, distance-based and parsimony-based placement methods were introduced such as UShER. These methods, in principle, scale linearly as the size of the reference tree grows. However, as the scale of genetic and genomic sequences continues to grow nearly exponentially, developing algorithms that can perform placement in sub-linear time while maintaining accuracy becomes more crucial. ResultsHere, we develop Splicer, the first such algorithm that can perform placement in guaranteed [Formula] time. To achieve this performance, Splicer first decomposes the original reference tree into blobs and constructs a phylogenetic scaffold tree linking representatives from different blobs. Every blob in such decomposition has at most [Formula] taxa, and the scaffold tree has at most [Formula] leaves, where c is any constant. Then, given the query sequences for placement, they are first placed onto a scaffold tree using pplacer or EPA-ng, and then placed more precisely within the respective blobs. We demonstrate the high accuracy of Splicer on an empirical influenza A virus dataset that has sparse coverage due to limited genomic surveillance. We also show that Splicer can, for the first time, apply maximum-likelihood placement to COVID-19 pandemic-scale data using a dataset with over 12 million SARS-CoV-2 reference genomes. Splicer scales the highly accurate maximum-likelihood approaches implemented in pplacer and EPA-ng to trees with millions of taxa and eliminates the necessity to curate and subsample genomic datasets for real-time classifications. Availability and implementationSplicer tool and source code are freely available at https://github.com/flu-crew/splicer.

bioinformatics↗

bioRxiv2025

Vaccine-induced antigenic drift of a human-origin H3N2 Influenza A virus in swine alters glycan binding and sialic acid avidity

Interspecies transmission of human influenza A viruses (FLUAV) to swine occurs frequently, yet the molecular factors driving adaptation remain poorly understood. Here we investigated how vaccine-induced immunity shapes the evolution of a human-origin H3N2 virus in pigs using an in vivo sustained transmission model. Pigs (seeders) were vaccinated with a commercial inactivated swine vaccine and then infected with an antigenically distinct FLUAV containing human-origin HA/NA. Contact pigs were introduced two days later. After 3 days, seeder pigs were removed, and new contacts introduced. This was repeated for a total of 4 contacts. Sequencing of nasal swab samples showed the emergence of mutations clustered near the HA receptor binding site, enabling immune escape and abolishing binding to N-glycolylneuraminic acid. Mutant viruses recognized 2,6-sialosides with 3 N-acetyllactosamine repeats, which are rare in swine lungs, while the parental virus bound structures with a minimum of 2 repeats. Adaptative HA mutations enhanced avidity for 2,6-linked sialic acid, likely compensating for the low abundance of extended glycans. Notably, residues outside the canonical HA binding pocket contribute to glycan binding, suggesting a trade-off between receptor breadth and avidity. These findings show that non-neutralizing immunity promotes viral adaptation by fine-tuning receptor engagement and immune evasion. SIGNIFICANCEUnderstanding how vaccination shapes influenza A virus (FLUAV) evolution across species barriers is critical for predicting and preventing zoonotic and reverse-zoonotic events. Our study demonstrates that vaccine-induced immune pressure can drive antigenic drift in a human-origin H3N2 virus, altering HA receptor binding properties that could inadvertently facilitate adaptation to swine. These changes shifted glycan specificity toward extended poly-LacNAc structures and enhanced 2,6-linked sialoglycans binding while abolishing Neu5Gc recognition. By revealing how non-neutralizing immunity fine-tunes HA-glycan interactions by engaging antigenically relevant residues in glycan binding, this work highlights vaccination as an underappreciated driver of host adaptation and viral evolution.

microbiology↗

bioRxiv2025

SmartHisto: Bayesian Active Learning for Histology Images

Accurate and efficient characterization of biological images is crucial for advancing systems biology and medical research. Recent advancements in deep learning and image processing have enabled neural network models to rapidly accelerate image analysis by utilizing large expert-annotated datasets. However, in histopathology, the size of whole-slide images makes expert annotation expensive, limiting the acquisition of sufficiently large annotated datasets and posing a major challenge for developing automated, AI-driven image analysis pipelines. To address this limitation, we propose a novel active learning-based framework to train image segmentation models interactively. Our approach employs a Bayesian neural network to identify informative regions in unlabeled images rather than entire images, making expert labeling more cost-effective. We validate our framework on multiple benchmark datasets spanning different staining techniques and magnifications, demonstrating substantial reductions in annotation effort. Notably, our method achieves a mean IoU of 0.75, significantly outperforming competing approaches, which average 0.60. Author summaryHistopathology is fundamental to investigating tissue and immune responses, host-pathogen interactions, and disease mechanisms. However, histopathology is highly resource-intensive and requires specialized training, dramatically increasing the costs of annotating whole-slide images and, consequently, the expenses of large-scale studies involving numerous labs and specialists. We developed a computational tool to overcome these challenges, implementing a robust uncertainty-based sampling algorithm in conjunction with a next-generation Bayesian Convolutional Neural Network. This algorithm can be used for hypothesis testing and discovery by reducing the reliance on large, precisely annotated training datasets required in automated image analysis pipelines. The base model, when trained to identify lung tissue types using a small set of annotated images, outperforms state-of-the-art models and can efficiently annotate thousands of images much more quickly than a human. Models trained by the proposed algorithm will serve as a standardized approach for pathologists and disease researchers to train automated image segmentation pipelines for large-scale histopathology.

bioinformatics↗

bioRxiv2025

The 2'-endo conformation of arabinose-CTP and arabinose-UTP inhibit viral polymerases by inducing long pauses.

Key to supporting human health in the face of evolving viruses is the development of novel antiviral drug scaffolds with the potential for broad inhibition of viral families. Nucleoside analogs are a key class of drugs that have demonstrated potential for the inhibition of several viral species. Here, we evaluate arabinose nucleotides (ara-NTP) as inhibitors of the SARS-CoV-2 and poliovirus polymerases using biochemistry, biophysics and structural biology. Ara-NTPs compete poorly with their natural counterparts for incorporation into RNA by viral polymerases. However, upon incorporation, ara-NMPs induce long polymerase pausing in both SARS-CoV-2 and poliovirus polymerase RNA elongation. Our studies suggest that subsequent nucleotide incorporation is inhibited at the catalytic step due to the 2-endo sugar pucker of the incorporated ara-NMP.

biochemistry↗

bioRxiv2025

Diverse Genomic Landscape of Swine Influenza A Virus in England (2014 - 2021)

Surveillance of influenza A viruses in pigs (SwIAV) is critical for identification of novel genetic groups that pose a risk to pig health and might have zoonotic potential. SwIAVs circulating in pigs in England between 2014 and 2021 were characterised using whole genome sequencing (WGS). Haemagglutinin (HA) and neuraminidase (NA) sequencing data from 82 of 368 influenza A positive samples (71 submissions) were determined, identifying H1N1 and H1N2 subtypes from the 1A classical swine and 1B human-seasonal lineages respectively. The 1B lineage viruses were predominant, accounting for 68.29% of sequenced viruses, with 1A lineage viruses comprising 31.71%, primarily from the 1A.3.3.2 clade (2009 H1N1 pandemic origin). This study characterised previously undefined diversity within the 1B lineage which led to the designation of new HA clades 1B.1.1.1, 1B.1.1.2 and 1B.1.1.3. Complete genome data were obtained from 64/82 viruses thereby updating the definition of genetic diversity thresholds and leading to the identification of 24 unique genotypes. All these 64 viruses contained PB2, PB1, PA, NP, MP, and NS gene segments of 2009 H1N1 pandemic origin. These data highlight the increasing divergence of SwIAV within pig populations England and emphasise the requirement for continued genomic surveillance to improve animal health and monitor zoonotic risk.

genomics↗

bioRxiv2025

The coronavirus helicase synergizes with the viral RNA polymerase to enable rapid RNA synthesis through duplex RNA

Positive-sense (+) RNA viruses often encode helicases presumed to support replication. Their precise role remains unresolved though, especially in coronaviruses (CoV) where the helicase translocates in the opposite direction to the polymerase. Using high-throughput single-molecule magnetic tweezers, we show that the coronavirus helicase enhances RNA synthesis through duplex RNA by tenfold, forming a directional complex with the viral polymerase. Despite opposing polarity, the helicase coordinates elongation by engaging the non-template strand. A detailed kinetic model derived from large datasets reveals distinct dynamic states, including fast bursting and slow, backtracking-prone modes, which are governed by helicase engagement. These results uncover an active coupling mechanism that modulates replication dynamics and provide a mechanistic basis for continuous versus discontinuous RNA synthesis in coronaviruses. Our findings establish the viral helicase as a central regulator of RNA replication rather than a passive accessory enzyme.

biophysics↗

bioRxiv2025

Sources and sinks of influenza A virus genomic diversity in swine from 2009 to 2022 in the United States

Influenza A virus (IAV) in swine in the U.S. is surveilled to monitor genetic evolution to inform intervention efforts and aid pandemic preparedness. We describe data from the U.S. Department of Agriculture National Surveillance Plan for Influenza A Virus in Pigs from 2009 to 2022. Clinical respiratory cases were subtyped followed by sequencing of hemagglutinin (HA) and neuraminidase (NA), and a subset of viruses were whole genome sequenced. Phylogenetic analysis identified geographic and temporal IAV reassortment hotspots. Regions acting as IAV genomic diversity sources or sinks were quantified, and dissemination was qualified and modeled. The dominant IAV clades were H1N2 (1B.2.1), H3N2 (1990.4.a), and H1N1 (H1-1A.3.3.3-c3). Internal genes were classified as triple-reassortant (T) or pandemic 2009 (P), and three genome constellations represented 73.5% of detections across the last two years. In some years, the distribution of IAV diversity was so narrowly distributed that it presented a statistical signal associated with local adaptation. We also demonstrated that the source of most IAV genomic diversity was in Midwest states (IL, MO, IA), and while this was correlated with swine inventory, the emergence and persistence of diversity was tied to swine transport across the U.S. The continued regional detection of unique HA, NA, and genome constellations provides support for targeted interventions to improve animal health and enhance pandemic preparedness. ImportanceVariation in the genetic diversity of influenza A virus (IAV) in swine through time and between regions impacts control efforts. This study quantified the genomic diversity of swine IAV collected from 2009-2022 at regional and national levels and modeled sources and sinks of that diversity. Seasonal patterns of IAV transmission were observed, and some locations contributed disproportionately to the emergence of genomic diversity. Minor groups of viruses had the potential to disseminate across the U.S. with animal movement. The identification of these patterns demonstrates the importance of a robust surveillance system to inform vaccine updates that reflect regional patterns of genetic diversity. We show how preemptive interventions in swine IAV diversity hubs could reduce reassortment and the emergence of novel genomic diversity, and how these efforts are likely to reduce the transmission of swine IAV within swine and between swine and humans.

microbiology↗

bioRxiv2025

A post-assembly conformational change makes the SARS-CoV-2 polymerase elongation-competent

Coronaviruses (CoV) encode sixteen non-structural proteins (nsps), most of which form the replication-transcription complex (RTC). The RTC contains a core composed of one nsp12 RNA-dependent RNA polymerase (RdRp), two nsp8s and one nsp7. The core RTC recruits other nsps to synthesize all viral RNAs within the infected cell. While essential for viral replication, the mechanism by which the core RTC assembles into a processive polymerase remains poorly understood. We show that the core RTC preferentially assembles by first having nsp12-polymerase bind to the RNA template, followed by the subsequent association of nsp7 and nsp8. Once assembled on the RNA template, the core RTC requires hundreds of seconds to undergo a conformational change that enables processive elongation. In the absence of RNA, the (apo-)RTC requires several hours to adopt its elongation-competent conformation. We propose that this obligatory activation step facilitates the recruitment of additional nsps essential for efficient viral RNA synthesis and may represent a promising target for therapeutic interventions.

biophysics↗

bioRxiv2024

Revealing reassortment in influenza A viruses with TreeSort

Reassortment among influenza A viruses (IAV) facilitates genomic evolution and has been associated with interspecies transmission and pandemics. We introduce a novel tool called TreeSort that accurately identifies recent and ancestral reassortment events on datasets with thousands of IAV whole genomes. The algorithm has immediate relevance to modern large-scale surveillance studies that generate thousands of whole genomes. TreeSort uses the phylogeny of a selected IAV segment as a reference and finds the branches on the phylogeny where reassortment has occurred with high probability by incorporating information from other gene segments. The tool reports the particular gene segments that were involved in reassortment and how different they are from prior gene pairings. Using TreeSort, we studied reassortment patterns of different IAV subtypes isolated in avian, swine, and human hosts. Avian IAV demonstrated more reassortment than human and swine IAV, with the avian H7 subtype displaying the most frequent reassortment. Reassortment in the swine and human H3 subtypes was more frequent than in the swine and human H1 subtypes, respectively. The highly pathogenic avian influenza H5N1 clade 2.3.4.4b had elevated reassortment rates in the 2020-2023 period; however, the surface protein-encoding genes (HA, NA, and MP) co-evolved together with almost no reassortment among these genes. We observed similar co-evolutionary patterns with very low rates of reassortment among the surface proteins for the human H1 and H3 lineages, suggesting that strong co-evolution and preferential pairings among surface proteins are a consequence of high viral fitness. Our algorithm enables real-time tracking of IAV reassortment within and across different hosts, can be applied to determine how specific genes evolve in response to reassortment events, and can identify novel viruses for pandemic risk assessment. TreeSort is available at https://github.com/flu-crew/TreeSort.

microbiology↗

bioRxiv2024

Exploring genetic signatures of zoonotic influenza A virus at the swine-human interface with phylogenetic and ancestral sequence reconstruction

Influenza A viruses (IAVs) in swine have zoonotic potential and pose a continuous threat of causing human pandemics, as demonstrated by the H1N1 pandemic in 2009. Despite increased genomic surveillance, we have limited knowledge of the IAV evolutionary dynamics leading to such zoonotic events and no clear understanding of genetic markers associated with interspecies transmission of IAV between humans and swine. To explore this, we analyzed a comprehensive publicly available whole genome dataset of human and swine IAV sequences. We conducted phylogenetic analyses and inference of ancestral host and sequence states for each IAV segment and mapped inferred mutations that were associated with transmission within and between swine and human hosts. We developed a custom python library to combine information from host and ancestral sequence annotated trees and applied statistical models to identify genetic markers associated with intra- or interspecies transmissions between swine and humans. This included analyzing mutation rates and the selective pressures acting on the viral proteins following intra- and interspecies transmissions and using a scalable, gradient-boosted decision tree machine learning approach to predict key amino acid positions critical for different transmission types. Our analyses indicated complex mutational patterns within and across viral proteins, but also suggested that specific protein regions and amino acid positions of especially several of the internal gene segments were more important for interspecies transmission. Our findings identify potential genetic signatures across the IAV proteins associated with host adaptation and zoonotic potential, offering valuable markers for early-warning genomic surveillance systems to enhance animal health and minimize the potential for zoonotic transmission of IAV.

bioinformatics↗

bioRxiv2024

PRRSV-2 variant classification: a dynamic nomenclature for enhanced monitoring and surveillance

Existing genetic classification systems for porcine reproductive and respiratory syndrome virus 2 (PRRSV-2), such as restriction fragment length polymorphisms (RFLPs) and sub-lineages, are unreliable indicators of genetic relatedness or lack sufficient resolution for epidemiological monitoring routinely conducted by veterinarians. Here, we outline a fine-scale classification system for PRRSV-2 genetic variants in the U.S. Based on >25,000 U.S. open-reading-frame 5 (ORF5) sequences, sub-lineages were divided into genetic variants using a clustering algorithm. Through classifying new sequences every three months and systematically identifying new variants across eight years, we demonstrated that prospective implementation of the variant classification system produced robust, reproducible results across time and can dynamically accommodate new genetic diversity arising from virus evolution. From 2015 and 2023, 118 variants were identified, with [~]48 active variants per year, of which 26 were common (detected >50 times). Mean within-variant genetic distance was 2.4% (max: 4.8%). The mean distance to the closest related variant was 4.9%. A routinely updated webtool (https://stemma.shinyapps.io/PRRSLoom-variants/) was developed and is publicly available for end-users to assign newly generated sequences to a variant ID. This classification system relies on U.S. sequences from 2015 onwards; further efforts are required to extend this system to older or international sequences. Finally, we demonstrate how variant classification can better discriminate between previous and new strains on a farm, determine possible sources of new introductions into a farm/system, and track emerging variants regionally. Adoption of this classification system will enhance PRRSV-2 epidemiological monitoring, research, and communication, and improve industry responses to emerging genetic variants. ImportanceThe development and implementation of a fine-scale classification system for PRRSV-2 genetic variants represents a significant advancement for monitoring PRRSV-2 occurrence in the swine industry. Based on systematically-applied criteria for variant identification using national-scale sequence data, this system addresses the shortcomings of existing classification methods by offering higher resolution and adaptability to capture emerging variants. This system provides a stable and reproducible method for classifying PRRSV-2 variants, facilitated by a freely available and regularly updated webtool for use by veterinarians and diagnostic labs. Although currently based on U.S. PRRSV-2 ORF5 sequences, this system can be expanded to include sequences from other countries, paving the way for a standardized global classification system. By enabling accurate and improved discrimination of PRRSV-2 genetic variants, this classification system significantly enhances the ability to monitor, research, and respond to PRRSV-2 outbreaks, ultimately supporting better management and control strategies in the swine industry.

microbiology↗

bioRxiv2024

A genus-specific nsp12 region impacts polymerase assembly in Alpha- and Gammacoronaviruses

Coronavirus relevancy for human health has surged over the past 20 years as they have a propensity for spillover into humans from animal reservoirs resulting in pandemics such as COVID-19. The diversity within the Coronavirinae subfamily and high infection frequency in animal species worldwide creates a looming threat that calls for research across all genera within the Coronavirinae subfamily. We sought to contribute to the limited structural knowledge within the Gammacoronavirus genera and determined the structure of the viral core replication-transcription complex (RTC) from Infectious Bronchitis Virus (IBV) using single-particle cryo-EM. Comparison between our IBV structure with published RTC structures from other Coronavirinae genera reveals structural differences across genera. Using in vitro biochemical assays, we characterized these differences and revealed their differing involvement in core RTC formation across different genera. Our findings highlight the value of cross-genera Coronavirinae studies, as they show genera specific features in coronavirus genome replication. A broader knowledge of coronavirus replication will better prepare us for future coronavirus spillovers.

biochemistry↗

bioRxiv2024

Experimental reproduction of viral replication and disease in dairy calves and lactating cows inoculated with highly pathogenic avian influenza H5N1 clade 2.3.4.4b

Highly pathogenic avian influenza (HPAI) H5N1 of the hemagglutinin clade 2.3.4.4b was detected in the United States in late 2021 and continues to circulate in all four North American flyways to date. In addition to impacting poultry, these HPAI viruses caused mortality events in wild bird species and wild mammals. Transmission in multiple host species raises the concern for mammalian adaptation. On March 25, 2024, HPAI H5N1 clade 2.3.4.4b was confirmed in a dairy cow in Texas in response to a multi-state investigation into milk production losses. Over one hundred positive herds were rapidly identified in Texas and eleven other U.S. states. The case description included reduced feed intake and rumen motility in lactating cows, decreased milk production, and thick yellow milk. The diagnostic investigation revealed detections of viral RNA in milk and mammary tissue with alveolar epithelial degeneration and necrosis, and positive immunoreactivity of glandular epithelium by immunohistochemistry. A single transmission event, likely from avian species to dairy cattle, followed by limited local transmission preceded the onward lateral transmission of H5N1 clade 2.3.4.4b genotype B3.13. We sought to experimentally reproduce infection with genotype B3.13 in Holstein yearling heifers and lactating cows. The heifers were inoculated by an aerosol respiratory route and the cows by an intramammary route. Clinical disease was mild in the heifers, but infection was confirmed by virus detection, lesions, and seroconversion. Clinical disease in lactating cows included decreased rumen motility, changes to milk appearance, and production losses consistent with field reports of viral mastitis. Infection was confirmed by high levels of viral RNA detected in milk, virus isolation, lesions in mammary tissue, and seroconversion. This study provides the foundation to investigate additional routes of infection, transmission, and intervention strategies.

microbiology↗

bioRxiv2024

Active surveillance for influenza A virus in swine reveals within-farm reassortment and cocirculation of distinct subtypes and genetic clades

Influenza A virus (IAV) is one of the three most frequently detected respiratory pathogens in swine. A passive IAV in swine surveillance system in the United States (U.S.) provides aggregated national metrics to quantify spatial and temporal changes in genetic diversity. However, swine production is not homogenous: production systems vary in size and management strategies that affect the transmission and evolution of IAV. To assess the impact of fine-scale variation in swine production on IAV transmission, we conducted active surveillance on sow farms and linked nurseries from 4 U.S. production systems for up to 14 monthly collections. From IAV-positive samples, we obtained 85 complete HA sequences, and of these, we successfully assembled 62 whole genomes with associated epidemiological information. To infer transmission and evolution, we conducted Bayesian phylodynamic analyses and detected six genetic clades from four HA lineages: the H1 1A classical swine, the H1 1B human-seasonal, and the H3 2010.1 and 1990.4 lineages. The 1B and H3 1990.4 strains showed evidence of transmission from sow farm to nursery. In contrast, 1A and H3 2010.1 viruses were detected in nurseries without detection in a linked sow farm. We also detected seven separate human-to- swine transmission events in the H1N1 pandemic clade (1A.3.3.2) in sow and nursery sites. Our data demonstrated that nursery sites were infected with IAV that was both linked and unlinked to the sow farm. These data suggest that control efforts may be impacted by subclinical IAV transmission in the breeding herd, the mixing of sow farm sources at the nursery, regional spread of new strains, and human-to-swine transmission. Regular surveillance activities within production systems provide the ability to match vaccine components to circulating diversity, thereby minimizing the opportunity for novel reassorted viruses to emerge and impact animal health.

bioinformatics↗